Socially Situated Planning (bibtex)
by Jonathan Gratch
Abstract:
Introduction: Virtual environments such as training simulators and video games do an impressive job at modeling the physical dynamics of synthetic worlds but fall short when modeling the social dynamics of anything but the most impoverished human encounters. Yet the social dimension is at least as important as good graphics for creating an engaging game or effective training tool. Commercial flight simulators accurately model the technical aspects of flight but many aviation disasters arise from social breakdowns: poor management skills in the cockpit, or the effects of stress and emotion. Perhaps the biggest consumer of simulation technology, the U.S. military, identifies unrealistic human and organizational behavior as a major limitation of existing simulation technology (NRC, 1998). And of course the entertainment industry has long recognized the importance of good character, emotional attachment and rich social interactions to "put butts in seats." This article describes a research effort to endow virtual training environments with richer models of social behavior. We have been developing autonomous and semi-autonomous software agents that plan and act while situated in a social network of other entities, human and synthetic (Hill et. al, 1997; Tambe, 1997; Gratch and Hill, 1999). My work has focused on making agents act in an organization and obey social constraints, coordinate their behavior, negotiate conflicts, but also obey their own self-interest and show a range of individual differences in their behavior and willingness to violate social norms, albeit within the relatively narrow context of a specific training exercise.
Reference:
Socially Situated Planning (Jonathan Gratch), Chapter in Socially Intelligent Agents, Multiagent Systems, Artificial Societies, and Simulated Organizations, volume 3, 2000.
Bibtex Entry:
@incollection{gratch_socially_2000,
	address = {AAAI Fall Symposium on Socially Intelligent Agents - The Human in the Loop, North Falmouth, MA},
	title = {Socially {Situated} {Planning}},
	volume = {3},
	url = {http://ict.usc.edu/pubs/Socially%20Situated%20Planning.pdf},
	abstract = {Introduction: Virtual environments such as training simulators and video games do an impressive job at modeling the physical dynamics of synthetic worlds but fall short when modeling the social dynamics of anything but the most impoverished human encounters. Yet the social dimension is at least as important as good graphics for creating an engaging game or effective training tool. Commercial flight simulators accurately model the technical aspects of flight but many aviation disasters arise from social breakdowns: poor management skills in the cockpit, or the effects of stress and emotion. Perhaps the biggest consumer of simulation technology, the U.S. military, identifies unrealistic human and organizational behavior as a major limitation of existing simulation technology (NRC, 1998). And of course the entertainment industry has long recognized the importance of good character, emotional attachment and rich social interactions to "put butts in seats." This article describes a research effort to endow virtual training environments with richer models of social behavior. We have been developing autonomous and semi-autonomous software agents that plan and act while situated in a social network of other entities, human and synthetic (Hill et. al, 1997; Tambe, 1997; Gratch and Hill, 1999). My work has focused on making agents act in an organization and obey social constraints, coordinate their behavior, negotiate conflicts, but also obey their own self-interest and show a range of individual differences in their behavior and willingness to violate social norms, albeit within the relatively narrow context of a specific training exercise.},
	booktitle = {Socially {Intelligent} {Agents}, {Multiagent} {Systems}, {Artificial} {Societies}, and {Simulated} {Organizations}},
	author = {Gratch, Jonathan},
	year = {2000},
	keywords = {Virtual Humans},
	pages = {181--188}
}
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